Lead Software Engineer - Databricks/PySpark/AI

We have an exciting and rewarding opportunity for you to take your data engineering career to the next level.

As a Lead Software Engineer - Databricks/PySpark/AI at JPMorganChase within the Corporate Sector-Global Finance team, you will serve as a senior hands-on developer and technical leader within an agile team, responsible for building, delivering, and optimizing cutting-edge data products that power agentic AI systems - autonomous AI agents capable of planning, reasoning, and executing multi-step tasks.

In this role, you will write production-quality code daily, drive implementation of essential technology solutions including data infrastructure, tool integrations, and retrieval systems that enable AI agents to access, interpret, and act on enterprise data in support of the firm's business goals.

You will be expected to mentor junior engineers, collaborate with cross-functional stakeholders, and champion engineering excellence through hands-on delivery.

Job Responsibilities


* Building and optimizing data pipelines and workflows that serve as the backbone for agentic AI systems, ensuring agents have reliable, real-time access to high-quality, structured and unstructured data


* Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.


* Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.


* Developing data retrieval and indexing layers that enable AI agents to autonomously search, query, and synthesize information across multiple data sources


* Building and maintaining tool-use infrastructure - APIs, data services, and function endpoints - that AI agents invoke to execute tasks, retrieve data, and interact with enterprise systems


* Implementing and enforcing best practices for data management, ensuring data quality, security, and compliance, including governance of data consumed and generated by autonomous AI agents


* Hands-on development of secure, high-quality production code following AWS best practices, and deploying efficiently using CI/CD pipelines;

Building orchestration and state management layers that support multi-step agent workflows, including memory, context persistence, and task chaining


* Writing and reviewing code daily, conducting thorough code reviews, and raising the technical bar across the team;

Mentoring and guiding junior and mid-level engineers through pairing, code reviews, and technical coaching


* Collaborating with prod...